Workshops Archive

Enhancing HPC Curriculum through Competitions

Workshop: 12th SC Workshop on Best Practices for HPC Training and Education

Authors: Cristina Carbunaru and Sriram Sami (National University of Singapore)

Abstract: High Performance Computing (HPC) is a critical driver of progress in artificial intelligence (AI), data-intensive science, and engineering. At the National University of Singapore, concepts of parallelism are taught in courses such as Parallel Computing and Parallel and Concurrent Programming. These provide strong theoretical foundations, but gaps remain in systems-level competencies, particularly in deploying, optimizing, and scaling applications on real HPC platforms. To address this, we introduced initiatives such as participation in student cluster competitions to train students in resource management, profiling, monitoring, and containerized workflows. This experiential learning bridges theory with operational expertise. Challenges include the steep learning curve of complex systems, limited access to shared infrastructure, and the need for up-to-date instructional expertise. Sustainable HPC curriculum development requires gradual expansion of topics, integration of hands-on training, and competition-driven learning. Formal HPC courses will enhance readiness for careers in computational science and AI, and foster cross-disciplinary collaboration.

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